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Sales forecastingDeloitte Analytics Approach
The growing worldof dataData has undoubtedly become the fuel for competitiveadvantage in the 21st century.Nowadays we generate and collect enormous volumes of dataand we are able to give machines the appropriate input forthem to learn and predict outcomes by using algorithms tointerpret raw data.Why sales forecastingSales forecasting allows companies to spot potential issues or risks and design appropriatecorrective actions to mitigate INANCIALPLANNINGSales forecasting helpssales managers planningtheir future activities,providing each of themwith a business plan formanaging their territory.Forecasting is the toolthat helps them identifingthe necessary customersto meet their targets.The sales forecast is thebest way to get a goodestimate of the productdemand. Sales teams arein the front line ofbusiness forecasting andbest positioned to gatherinformation aboutanticipated demandThe more accurate thesales forecast, the betterprepared your companywill be to manage itsinventory, avoiding bothoverstock and stock-outsituations. Stableinventory also meansbetter management ofyour productionAnticipating sales givesmanagers theinformation they need topredict revenue andprofit. Having goodforecasting informationgives a company theability to explorepossibilities to rise bothrevenue and net GHTSMARKETINGBENEFITSHaving an insight on theprojected productionrates gives the possibilityto have a better controlof the internaloperations. Byanticipating future sales,managers can makedecisions about hiring,marketing and expansionContinuous improvementis a goal of many if not allbusinesses. Byforecasting sales andcontinually revisingprocesses to increaseaccuracy, companies canimprove all aspects oftheir businessperformanceAccurate salesforecasting can help youtracking data and gaininginsights into areas whereimprovements can bemade. Furthermore, itcan help understandingthe customers’ behaviourin order to increaseconversion ratesSales forecasting givesmarketing an importantlook at future sales.This offers theopportunity to schedulepromotions if sales areexpected to be too weak
Principles for a great Sales ForecastUSE EXTERNAL DATAINVOLVE BUSINESS EXPERTSRobust predictions benefit from havinghigh quality and easily accessible data.These data can be enriched with externalsources that can contribute improving thequality of the predictions. Depending onthe product of the company, differentkinds of external data could be used.Below are some examples of openexternal data: income-age geographical distribution blogs or social networks articles macro-economic factors sector indexesSales forecasting is not a one-time activity,but an ongoing process that affects everyaspect of the sales pipeline. Therefore, it isimportant not only to make predictionsbased on the numbers on hand but alsoto pair these numbers with qualitativeinformation in order to get a more realisticview of the business. This can be achievedwith appropriate communication andcollaboration between the business andthe team involved in the construction ofthe forecasting -20%0-25%M 1M 2M 3M 4M 5DEVIATIONM 6REALM 7M 8M 9M 10FORECASTDEFINE CLEAR NEEDSBE FLEXIBLE TO CHANGEThe key phase in creating a salesforecasting solution is the understandingand the definition of the business needs:this allows to delimit the perimeter of whatis requested, what can be achieved andhow it can be achieved. Businessknowledge is essential to define the mostappropriate analytics tool.It is impossible to use a single model thatwill ensure the track of the exact terms,time, and context of every sale. Instead,companies should focus on developing aprocess that can be managed, reevaluated, and modified as conditionschange.
ORMATIONCOMPARINGEXPECTATIONS1PROBLEM DEFINITIONIdentify the main business goals and setexpectations before any development phase.2DATA GATHERING & PREPARATIONSearch and preprocess the data to define andintegrate the different data sources that will beused as foundation for the models.Data preparation is one of the most important andcritical phases in a data mining project: data needsto be effectively interpreted and analysed.3EXPLORATORY DATA ANALYSISPrimary analyses are carried out on data in orderto use insights from results to define further steps.The KPIs that should be used in the machinelearning models would be individuated and itwould be assessed how they are related to eachother.4MACHINE LEARNINGThe process of applying statistical algorithms onprepared dataset, providing a rigorous frameworkto test those models.Insights drawn from previous phases are used tochoose the most appropriate models that could beapplied, evaluate pros and cons and implement thesolution.5VALIDATION & TESTINGAssess models’ accuracy and robustness. Asmodels are used to forecast future sales, theyshould be generalized and be able to give reliableresults outside of the dataset they have beendeveloped on.6RESULTS COMMUNICATIONCommunicate effectively the advanced analyticsmodels results and translate them into actionablebusiness insights. Models results should assistbusiness in decision-making.
Deloitte Analyticspossible enhancementsHaving a sales predictive model is the first step towards creating adata-driven company. Alongside the predictive model, it is advisableto adopt a series of tools to support decisional business processes.MONITORING TOOLBuilding dashboards that visualize predictedresults and comparisons with previous yearsis a key tool for business users interested inmonitoring the actual performance of thecompany.KPIs REPORTINGIt is important to create a tool that gives usersthe possibility to analyze KPIs and detectmisalignments or deviation from expectedvalues or targets (e.g.: early-warning, alerts,traffic light charts ).PRESCRIPTIVE ANALYSISPrescriptive Analytics extends beyondpredictive analytics by specifying both theactions necessary to achieve predictedoutcomes and the interrelated effects of eachdecision. This kind of analysis is able to answerquestions such as “what do we need to do toachieve a specific forecast?”TOOLS FOR DEVELOPING ANDREPORTING SALES FORECASTINGDeloitte Analytics has a vast knowledge oftechnical tools for data management, datamodelling and reporting in Sales Forecasting.Access to relevant data-driven insights is anecessity not only to formulate an effectivebusiness strategy, but also to monitor itsexecution.
ContactsAlfredo Maria GaribaldiPartner Analytics Country Leaderagaribaldi@deloitte.itDaniele Pier Giorgio BobbaPartnerdbobba@deloitte.itMarco LeaniPartnermleani@deloitte.itAlberto FerrarioDirectoralferrario@deloitte.itOur national team of over 200 professionals has proven experience in structuring,managing, and delivering Enterprise Information Management strategies andimplementation services. Through the collective experience of local practice and leveragingassets and best practices of our global WW Deloitte Analytics team, we have serve ourcustomers with a broad array of toolkits, accelerators, models, leading-edge practices,diagnostics, and governance approaches to accelerate and improve the quality of EIMprojects and ensure a focus on value creation.Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private companylimited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTLand each of its member firms are legally separate and independent entities. DTTL (alsoreferred to as “Deloitte Global”) does notprovide services to clients. Please see www.deloitte.com/about for a more detaileddescription of DTTL and its member firms. 2018 Deloitte Consulting Srl
Communicate effectively the advanced analytics models results and translate them into actionable business insights. Models results should assist business in decision-making. 1 6 5 4 3 2 The growing world of data. Principles for a great Sales Forecast Data has undoubtedly become the fuel for competitive
